Update app.py

app.py

@@ -3,13 +3,14 @@ import numpy as np
 import random
 from diffusers import DiffusionPipeline
 import torch
+import spaces
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 if torch.cuda.is_available():
     torch.cuda.max_memory_allocated(device=device)
     pipe = DiffusionPipeline.from_pretrained("Yntec/DreamPhotoGASM", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
-    pipeline.load_lora_weights("ovieyra21/autotrain-begg7-ozit5")
+    pipe.load_lora_weights("ovieyra21/autotrain-begg7-ozit5")
     pipe.enable_xformers_memory_efficient_attention()
     pipe = pipe.to(device)
 else: 
@@ -19,21 +20,21 @@ else:
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
+@spaces.GPU(duration=120)
 def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
-
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
         
     generator = torch.Generator().manual_seed(seed)
     
     image = pipe(
-        prompt = prompt, 
-        negative_prompt = negative_prompt,
-        guidance_scale = guidance_scale, 
-        num_inference_steps = num_inference_steps, 
-        width = width, 
-        height = height,
-        generator = generator
+        prompt=prompt, 
+        negative_prompt=negative_prompt,
+        guidance_scale=guidance_scale, 
+        num_inference_steps=num_inference_steps, 
+        width=width, 
+        height=height,
+        generator=generator
     ).images[0] 
     
     return image
@@ -44,20 +45,16 @@ examples = [
     "A delicious ceviche cheesecake slice",
 ]
 
-css="""
+css = """
 #col-container {
     margin: 0 auto;
     max-width: 520px;
 }
 """
 
-if torch.cuda.is_available():
-    power_device = "GPU"
-else:
-    power_device = "CPU"
+power_device = "GPU" if torch.cuda.is_available() else "CPU"
 
 with gr.Blocks(css=css) as demo:
-    
     with gr.Column(elem_id="col-container"):
         gr.Markdown(f"""
         # Text-to-Image Gradio Template
@@ -65,8 +62,7 @@ with gr.Blocks(css=css) as demo:
         """)
         
         with gr.Row():
-            
-            prompt = gr.Text(
+            prompt = gr.Textbox(
                 label="Prompt",
                 show_label=False,
                 max_lines=1,
@@ -79,8 +75,7 @@ with gr.Blocks(css=css) as demo:
         result = gr.Image(label="Result", show_label=False)
 
         with gr.Accordion("Advanced Settings", open=False):
-            
-            negative_prompt = gr.Text(
+            negative_prompt = gr.Textbox(
                 label="Negative prompt",
                 max_lines=1,
                 placeholder="Enter a negative prompt",
@@ -98,7 +93,6 @@ with gr.Blocks(css=css) as demo:
             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
             
             with gr.Row():
-                
                 width = gr.Slider(
                     label="Width",
                     minimum=256,
@@ -116,7 +110,6 @@ with gr.Blocks(css=css) as demo:
                 )
             
             with gr.Row():
-                
                 guidance_scale = gr.Slider(
                     label="Guidance scale",
                     minimum=0.0,
@@ -134,14 +127,14 @@ with gr.Blocks(css=css) as demo:
                 )
         
         gr.Examples(
-            examples = examples,
-            inputs = [prompt]
+            examples=examples,
+            inputs=[prompt]
         )
 
     run_button.click(
-        fn = infer,
-        inputs = [prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
-        outputs = [result]
+        fn=infer,
+        inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+        outputs=[result]
     )
 
-demo.queue().launch()
+demo.queue().launch()